Termite Mounds and Chitemene Agriculture: A Statistical Analysis of Their Association in Southwestern Tanzania

1982 ◽  
Vol 9 (6) ◽  
pp. 499 ◽  
Author(s):  
Howard W. Mielke ◽  
Paul W. Mielke
Keyword(s):  
Statistical Analysis ◽  
Termite Mounds

Termite mounds may not be foraging hotspots for mega-herbivores in a nutrient-rich matrix

2013 ◽  
Vol 29 (6) ◽  
pp. 551-558 ◽  
Author(s):  
Justice Muvengwi ◽  
Monicah Mbiba ◽  
Tatenda Nyenda
Keyword(s):  
Statistical Analysis ◽  
Tree Species ◽  
Plant Biomass ◽  
Wiener Index ◽  
Tree Species Diversity ◽  
Termite Mounds ◽  
Mammalian Herbivores ◽  
Biomass Removal ◽  
Species Specific ◽  
And Control

Abstract:Our study investigated the influence of termitaria on vegetation utilization by elephants in Chewore North, Zimbabwe. Ten termite mounds and ten similar sized control plots were surveyed for soil nutrients, tree species diversity and plant biomass removal by elephants. Termite mounds had higher mean (± SE) concentrations of P, Ca, Mg and Na (0.15 ± 0.01, 48.8 ± 9.32, 5.78 ± 1.59 and 0.47 ± 0.12 meq per 100 g respectively) than control plots (0.05 ± 0.01, 3.33 ± 0.56, 1.53 ± 0.22 and 0.19 ± 0.02 meq per 100 g). However, Shannon Wiener index of tree diversity did not vary significantly between termite mounds (1.13 ± 0.280) and their control plots (0.827 ± 0.469). Contrary to most studies investigating patterns of vegetation utilization by large mammalian herbivores on termitaria, biomass removal was five times more on control plots than termite mounds. No difference in biomass removal was noted for Colophospermum mopane which had enough replicates for statistical analysis both on termite mounds and control plots. Our study negates the hypothesis that nutrient-rich soil patches will act as feeding hotspots for large mammalian herbivores. We concluded that vegetation utilization by elephants may be tree species specific, particularly in nutrient-rich environments.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Intraindividual Variability in Development Within and Between Individuals

2001 ◽  
Vol 6 (3) ◽  
pp. 187-193 ◽  
Author(s):  
John R. Nesselroade
Keyword(s):  
Statistical Analysis ◽  
Research Design ◽  
Intraindividual Variability ◽  
Factor Analytic

A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.

Review of Basic FORTRAN for Statistical Analysis.

1967 ◽  
Vol 12 (9) ◽  
pp. 467-467
Author(s):  
JOHN C. LOEHLIN
Keyword(s):  
Statistical Analysis
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